Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few wo...Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.展开更多
Based on the point spread function （PSF） theory, the side-lobe extension direction of the impulse response in bistatic synthetic aperture radar （BSAR） is analyzed in detail; in addition, the corresponding autofocu...Based on the point spread function （PSF） theory, the side-lobe extension direction of the impulse response in bistatic synthetic aperture radar （BSAR） is analyzed in detail; in addition, the corresponding autofocus in BSAR should be considered along iso-range direction, not the traditional azimuth resolution （AR） direction. The conclusion is verified by the computer simulation.展开更多
A point spread function（PSF） for the blurring component in positron emission tomography（PET） is studied. The PSF matrix is derived from the single photon incidence response function. A statistical iterative recons...A point spread function（PSF） for the blurring component in positron emission tomography（PET） is studied. The PSF matrix is derived from the single photon incidence response function. A statistical iterative reconstruction（IR） method based on the system matrix containing the PSF is developed. More specifically, the gamma photon incidence upon a crystal array is simulated by Monte Carlo（MC） simulation, and then the single photon incidence response functions are calculated. Subsequently, the single photon incidence response functions are used to compute the coincidence blurring factor according to the physical process of PET coincidence detection. Through weighting the ordinary system matrix response by the coincidence blurring factors, the IR system matrix containing the PSF is finally established. By using this system matrix, the image is reconstructed by an ordered subset expectation maximization（OSEM） algorithm. The experimental results show that the proposed system matrix can substantially improve the image radial resolution, contrast,and noise property. Furthermore, the simulated single gamma-ray incidence response function depends only on the crystal configuration, so the method could be extended to any PET scanner with the same detector crystal configuration.展开更多
A set of point spread functions (PSF) has been obtained by means of Monte-Carlo simulation for asmall gamma camera with a pinhole collimator of various hole diameters. The FOV (field of view) of the camera isexpended ...A set of point spread functions (PSF) has been obtained by means of Monte-Carlo simulation for asmall gamma camera with a pinhole collimator of various hole diameters. The FOV (field of view) of the camera isexpended from 45 mm to 70 mm in diameter. The position dependence of the variances of PSF is presented, and theacceptance for the 140 kev gamma rays is explored. A phantom of 70 mm in diameter was experimentally imaged inthe camera with effective FOV of only 45 mm in diameter.展开更多
空间变化PSF(Space-variant Point Spread Function,SVPSF)图像,即物空间各点的退化随位置的改变而改变的图像,由于其复原技术涉及到多个甚至海量PSF的提取、存储和运算,相对于空间不变PSF(Space-Invariant Point Spread Function,SIPSF...空间变化PSF(Space-variant Point Spread Function,SVPSF)图像,即物空间各点的退化随位置的改变而改变的图像,由于其复原技术涉及到多个甚至海量PSF的提取、存储和运算,相对于空间不变PSF(Space-Invariant Point Spread Function,SIPSF)图像复原要困难得多。目前处理此类图像的主要方法包括空间坐标转换法,等晕区分块复原法,以减少数据存储量,降低计算量,提高收敛速度为目标的直接复原法等。本文回顾了这一课题的研究历史,对目前的研究工作进行了分析和总结,介绍了本实验室提出的结合GRM(Gradient Ringing Metric)评价算法的总变分最小化图像分块复原法,并提出了未来工作关注重点的展望。展开更多
为提高非高斯分布星点定位的精度,提出了一种新的PSFC(point spread function correlation)星点定位算法,具有很好的抗噪性能和精度水平,易于工程实现.该算法利用互相关中的定义,通过确定系统所测定的PSF与星像灰度值之间的最大相似度...为提高非高斯分布星点定位的精度,提出了一种新的PSFC(point spread function correlation)星点定位算法,具有很好的抗噪性能和精度水平,易于工程实现.该算法利用互相关中的定义,通过确定系统所测定的PSF与星像灰度值之间的最大相似度来定位星点位置,PSF的测定是在作互相关计算之前全视场范围内可按照整像素和亚像素两种方式完成的.仿真实验结果表明:在带有噪声的星像图条件下,本文PSF相关法的定位精度最高可达到0.034像素,比质心法的精度提高1个数量级,比曲面拟合法的精度提高约20%.展开更多
基于快速傅里叶变换的快速迭代收缩阈值算法(fast iterative shrinkage threshold algorithm based on fast Fourier transform, FFT-FISTA)具有较高的计算效率,但其忽略点扩散函数的空间变化及卷绕误差,造成声源识别性能的损失,为此提...基于快速傅里叶变换的快速迭代收缩阈值算法(fast iterative shrinkage threshold algorithm based on fast Fourier transform, FFT-FISTA)具有较高的计算效率,但其忽略点扩散函数的空间变化及卷绕误差,造成声源识别性能的损失,为此提出基于函数波束形成的改进FFT-FISTA算法。改进算法以函数波束形成输出作为FFT-FISTA算法的迭代输入,建立函数波束形成、声源分布及升幂空间转移不变点扩散函数的线性方程组,基于周期边界条件下的快速傅里叶变换进行迭代求解,使被运算的非周期函数变为一个周期函数,解决补零边界带来的波数泄漏问题,可提高运算准确性,进一步提升成像性能;通过指数运算锐化点扩散函数主瓣,拓展点扩散函数空间转移不变性假设的适用性。仿真和试验结果表明,相较于常规FFT-FISTA算法,改进算法能提升成像空间分辨率及动态范围,扩大FFT-FISTA算法的有效成像区域,压缩气体泄漏试验结果验证了改进算法的有效性。展开更多
This study was to assess quantitatively the accuracy of ^(18)F-FDG PET/CT images reconstructed by TOF+PSF and TOF only, considering the noise-matching concept to minimize probable bias in evaluating algorithm performa...This study was to assess quantitatively the accuracy of ^(18)F-FDG PET/CT images reconstructed by TOF+PSF and TOF only, considering the noise-matching concept to minimize probable bias in evaluating algorithm performance caused by noise. PET images of similar noise level were considered. Measurements were made on an inhouse phantom with hot inserts of Φ10–37 mm, and oncological images of 14 patients were analyzed. The PET images were reconstructed using the OSEM, OSEM+TOF and OSEM+TOF+PSF algorithms. Optimal reconstruction parameters including iteration, subset, and FWHM of post-smoothing filter were chosen for both the phantom and patient data. In terms of quantitative accuracy, the recovery coefficient(RC) was calculated for the phantom PET images. The signal-to-noise ratio(SNR),lesion-to-background ratio(LBR), and SUV_(max)were evaluated from the phantom and clinical data. The smallest hot insert(Ф10 mm) with 2:1 activity concentration ratio could be detected in the PET image reconstructed using the TOF and TOF+PSF algorithms, but not the OSEM algorithm. The relative difference for SNR between the TOF+PSF and OSEM showed significantly higher values for smaller sizes, while SNR change was smaller for Ф22–37 mm inserts both 2:1 and 4:1 activity concentration ratio. In the clinical study, SNR gains were 1.6 ± 0.53 and 2.7 ± 0.74 for the TOF and TOF+PSF, while the relative difference of contrast was 17 ± 1.05 and 41.5 ± 1.85% for the TOF only and TOF+PSF, respectively. The impact of TOF+PSF is more significant than that of TOF reconstruction, in smaller inserts with low activity concentration ratio. In the clinical PET/CT images, the use of the TOF+PSF algorithm resulted in better SNR and contrast for lesions, and the highest SUV_(max)was also seen for images reconstructed with the TOF+PSF algorithm.展开更多
基金the Postdoctoral ScienceFoundation of China(No.2023M730156)the NationalNatural Foundation of China(No.62301012).
文摘Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.
文摘Based on the point spread function （PSF） theory, the side-lobe extension direction of the impulse response in bistatic synthetic aperture radar （BSAR） is analyzed in detail; in addition, the corresponding autofocus in BSAR should be considered along iso-range direction, not the traditional azimuth resolution （AR） direction. The conclusion is verified by the computer simulation.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.Y4811H805C and 81101175)
文摘A point spread function（PSF） for the blurring component in positron emission tomography（PET） is studied. The PSF matrix is derived from the single photon incidence response function. A statistical iterative reconstruction（IR） method based on the system matrix containing the PSF is developed. More specifically, the gamma photon incidence upon a crystal array is simulated by Monte Carlo（MC） simulation, and then the single photon incidence response functions are calculated. Subsequently, the single photon incidence response functions are used to compute the coincidence blurring factor according to the physical process of PET coincidence detection. Through weighting the ordinary system matrix response by the coincidence blurring factors, the IR system matrix containing the PSF is finally established. By using this system matrix, the image is reconstructed by an ordered subset expectation maximization（OSEM） algorithm. The experimental results show that the proposed system matrix can substantially improve the image radial resolution, contrast,and noise property. Furthermore, the simulated single gamma-ray incidence response function depends only on the crystal configuration, so the method could be extended to any PET scanner with the same detector crystal configuration.
基金Supported by the National Natural Science Foundation of China(10275063)
文摘A set of point spread functions (PSF) has been obtained by means of Monte-Carlo simulation for asmall gamma camera with a pinhole collimator of various hole diameters. The FOV (field of view) of the camera isexpended from 45 mm to 70 mm in diameter. The position dependence of the variances of PSF is presented, and theacceptance for the 140 kev gamma rays is explored. A phantom of 70 mm in diameter was experimentally imaged inthe camera with effective FOV of only 45 mm in diameter.
文摘空间变化PSF(Space-variant Point Spread Function,SVPSF)图像,即物空间各点的退化随位置的改变而改变的图像,由于其复原技术涉及到多个甚至海量PSF的提取、存储和运算,相对于空间不变PSF(Space-Invariant Point Spread Function,SIPSF)图像复原要困难得多。目前处理此类图像的主要方法包括空间坐标转换法,等晕区分块复原法,以减少数据存储量,降低计算量,提高收敛速度为目标的直接复原法等。本文回顾了这一课题的研究历史,对目前的研究工作进行了分析和总结,介绍了本实验室提出的结合GRM(Gradient Ringing Metric)评价算法的总变分最小化图像分块复原法,并提出了未来工作关注重点的展望。
文摘为提高非高斯分布星点定位的精度,提出了一种新的PSFC(point spread function correlation)星点定位算法,具有很好的抗噪性能和精度水平,易于工程实现.该算法利用互相关中的定义,通过确定系统所测定的PSF与星像灰度值之间的最大相似度来定位星点位置,PSF的测定是在作互相关计算之前全视场范围内可按照整像素和亚像素两种方式完成的.仿真实验结果表明:在带有噪声的星像图条件下,本文PSF相关法的定位精度最高可达到0.034像素,比质心法的精度提高1个数量级,比曲面拟合法的精度提高约20%.
文摘基于快速傅里叶变换的快速迭代收缩阈值算法(fast iterative shrinkage threshold algorithm based on fast Fourier transform, FFT-FISTA)具有较高的计算效率,但其忽略点扩散函数的空间变化及卷绕误差,造成声源识别性能的损失,为此提出基于函数波束形成的改进FFT-FISTA算法。改进算法以函数波束形成输出作为FFT-FISTA算法的迭代输入,建立函数波束形成、声源分布及升幂空间转移不变点扩散函数的线性方程组,基于周期边界条件下的快速傅里叶变换进行迭代求解,使被运算的非周期函数变为一个周期函数,解决补零边界带来的波数泄漏问题,可提高运算准确性,进一步提升成像性能;通过指数运算锐化点扩散函数主瓣,拓展点扩散函数空间转移不变性假设的适用性。仿真和试验结果表明,相较于常规FFT-FISTA算法,改进算法能提升成像空间分辨率及动态范围,扩大FFT-FISTA算法的有效成像区域,压缩气体泄漏试验结果验证了改进算法的有效性。
基金supported by the Tehran University of Medical Sciences,Tehran,Iran(No.24166)the Masih Daneshvari Hospital,Shahid Beheshti University of Medical Sciences,Tehran,Iran
文摘This study was to assess quantitatively the accuracy of ^(18)F-FDG PET/CT images reconstructed by TOF+PSF and TOF only, considering the noise-matching concept to minimize probable bias in evaluating algorithm performance caused by noise. PET images of similar noise level were considered. Measurements were made on an inhouse phantom with hot inserts of Φ10–37 mm, and oncological images of 14 patients were analyzed. The PET images were reconstructed using the OSEM, OSEM+TOF and OSEM+TOF+PSF algorithms. Optimal reconstruction parameters including iteration, subset, and FWHM of post-smoothing filter were chosen for both the phantom and patient data. In terms of quantitative accuracy, the recovery coefficient(RC) was calculated for the phantom PET images. The signal-to-noise ratio(SNR),lesion-to-background ratio(LBR), and SUV_(max)were evaluated from the phantom and clinical data. The smallest hot insert(Ф10 mm) with 2:1 activity concentration ratio could be detected in the PET image reconstructed using the TOF and TOF+PSF algorithms, but not the OSEM algorithm. The relative difference for SNR between the TOF+PSF and OSEM showed significantly higher values for smaller sizes, while SNR change was smaller for Ф22–37 mm inserts both 2:1 and 4:1 activity concentration ratio. In the clinical study, SNR gains were 1.6 ± 0.53 and 2.7 ± 0.74 for the TOF and TOF+PSF, while the relative difference of contrast was 17 ± 1.05 and 41.5 ± 1.85% for the TOF only and TOF+PSF, respectively. The impact of TOF+PSF is more significant than that of TOF reconstruction, in smaller inserts with low activity concentration ratio. In the clinical PET/CT images, the use of the TOF+PSF algorithm resulted in better SNR and contrast for lesions, and the highest SUV_(max)was also seen for images reconstructed with the TOF+PSF algorithm.
